
Web Data Management
A Warehouse Approach
Springer (Publisher)
Published on 14. December 2011
Book
Paperback/Softback
XXI, 465 pages
978-1-4419-1806-2 (ISBN)
Description
Existence of huge amounts of data on the Web has developed an
undeferring need to locate right information at right time, as well as
to integrating information effectively to provide a comprehensive
source of relevant information.
There is a need to develop efficient tools for analyzing and managing
Web data, and efficiently managing Web information from the database
perspective. The book proposes a data model called WHOM (Warehouse
Object Model) to represent HTML and XML documents in the warehouse. It
defines a set of web algebraic operators for building new web tables
by extracting relevant data from the Web, as well as generating new
tables from existing ones. These algebraic operators are used for
change detection.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2004
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
35 s/w Abbildungen
XXI, 465 p. 35 illus.
Dimensions
Height: 254 mm
Width: 178 mm
Thickness: 27 mm
Weight
909 gr
ISBN-13
978-1-4419-1806-2 (9781441918062)
DOI
10.1007/b97475
Schweitzer Classification
Other editions
Additional editions

E-Book
05/2006
Springer
€76.99
Available for download

Book
11/2003
Springer
€78.06
Shipment within 5-7 days
Persons
Sourav S Bhowmick
Sourav S. Bhowmick is an Associate Professor in the School of Computer Science and Engineering (SCSE) at Nanyang Technological University, Singapore. His core research expertise is in data management, human-data interaction, and data analytics. His research has appeared in premium venues such as ACM SIGMOD, VLDB, ACM WWW, ACM MM, ACM SIGIR, The VLDB Journal, Bioinformatics, and Biophysical Journal. He is co-recipient of Best Paper Awards in ACM CIKM 2004, ACM BCB 2011, and VLDB 2021 for work on mining structural evolution of tree-structured data, generating functional summaries, and scalable attributed network embedding, respectively. He is a co-recipient of 2021 ACM SIGMOD Research Highlights Award. Sourav serves as a member of the SIGMOD Executive Committee, is a regular member of the PVLDB Advisory Board, and co-leads the committee for Diversity and Inclusion in Database Conference Venues. In 2018, he was a co-recipient of theVLDB Service Award from the VLDB Endowment. He was inducted into Distinguished Members of the ACM in 2020.
Byron Choi
Byron Choi is the Associate Head and an Associate Professor at the Department of Computer Science at Hong Kong Baptist University (HKBU). His research interests include graph-structured databases, database usability, database security, and time series analysis. Byron's publications have appeared in premium venues such as TKDE, VLDBJ, SIGMOD, PVLDB/VLDB, and ICDE. He has served as a program committee member or reviewer of premium conferences and journals, including PVLDB, VLDBJ, ICDE, IEEE TKDE, and ACM TOIS. He was recognized as a distinguished program committee (PC) member by ACM SIGMOD 2021 and received a best reviewer award from ACM CIKM 2021 and distinguished reviewer award from PVLDB 2019. He served as the director of a Croucher Foundation Advanced Study Institute (ASI) program titled "Frontiers in Big Data Graph Research"in 2015 and was a recipient of the HKBU President's Award for Outstanding Young Researcher in 2016.
Content
A Survey of Web Data Management Systems.- Node and Link Objects.- Predicates on Node and Link Objects.- Imposing Constraints on Hyperlink Structures.- Query Mechanism for the Web.- Schemas for Warehouse Data.- WHOM-Algebra.- Web Data Visualization.- Detecting and Representing Relevant Web Deltas.- Knowledge Discovery Using Web Bags.- The Road Ahead.